System and method for narrowband pre-detection signal processing for passive coherent location applications

ABSTRACT

A system and method for narrowband pre-detection signal processing in passive coherent location applications is disclosed. A receiving subsystem receives a reference signal and a target signal from an uncontrolled transmitter. The target signal is reflected from a target. The passive coherent location system includes subprocessors that perform pre-detection operations on the reference and target signals. The functions include zero-doppler cancellation, quadrature demodulation, reference beam regeneration, coherent processing interval selection, power spectral density estimation, cross ambiguity function formation, and the like. Within these operations, the reference signal is filtered with respect to the target signal to form a first output reference signal. The first output reference signal is combined with the first target signal to form a first output target signal. The output target signal then is used for subsequent passive coherent location processing operations. The filter is updated with respect to a difference between the target signal and a subsequent target signal. Further, two paths are used for correlation processing of the reference and target signals.

CROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application claims benefit of U.S. Provisional PatentApplication No. 60/288,452 entitled System and Method for NarrowbandPre-Detection Signal Processing for PCL Applications, filed May 4, 2001that is hereby incorporated by reference.

BACKGROUND OF THE INVENTION

[0002] 1. Field of the Invention

[0003] The present invention relates to a passive coherent location(PCL) system, and more particularly, to a system and method fornarrowband pre-detection signal processing for PCL applications.

[0004] 2. Discussion of the Related Art

[0005] Radar systems detect the presence of a target of interest andprovide information about that target. Conventional radar systemsinclude pulsed radar and continuous wave radar. In pulsed radar, themeasure of target distance is determined by the measurement of the timeelapsed from the transmission of an electromagnetic energy pulse to thereception of its reflected energy. In continuous wave radar, acontinuous wave is transmitted. The target distance is determinedthrough the measurement of the frequency shift between the transmittedsignal and the received reflected signal.

[0006] Conventional radar systems transmit electromagnetic energy. Aportion of the transmitted electromagnetic energy is reflected off atarget of interest and scattered in the space. The radar system receivesthe reflected energy and extracts the information about the target ofinterest by correlating the received reflected energy with replicas ofthe transmitted energy.

SUMMARY OF THE INVENTION

[0007] Accordingly, the present invention is directed to a PCLapplication and method for signal processing for PCL application.

[0008] A system and method for narrowband pre-detection signalprocessing in passive coherent location applications is disclosed. Areceiving subsystem receives a reference signal and a target signal froman uncontrolled transmitter. The target signal is reflected from atarget. The passive coherent location system includes subprocessors thatperform pre-detection operations on the reference and target signals.The functions include zero-doppler cancellation, quadraturedemodulation, reference beam regeneration, coherent processing intervalselection, power spectral density estimation, cross ambiguity functionformation, and the like. Within these operations, the reference signalis filtered with respect to the target signal to form a first outputreference signal. The first output reference signal is combined with thefirst target signal to form a first output target signal. The outputtarget signal then is used for subsequent passive coherent locationprocessing operations. The filter is updated with respect to adifference between the target signal and a subsequent target signal.Further, two paths are used for correlation processing of the referenceand target signals.

[0009] Additional features and advantages of the invention will be setforth in the description that follows, and in part will be apparent fromthe description, or may be learned by practice of the invention. Theobjectives and other advantages of the invention will be realized andattained by the structure particularly pointed out in the writtendescription and claims hereof as well as the appended drawings.

[0010] It is to be understood that both the foregoing generaldescription and the following detailed description are exemplary andexplanatory and are intended to provide further explanation of theinvention as claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The accompanying drawings, which are included to provide furtherunderstanding of the invention and are incorporated in and constitutes apart of this specification, illustrate embodiments of the invention andtogether with the description serves to explain the principles of theinvention. In the drawings:

[0012]FIG. 1 illustrates a block diagram of a passive coherent locationsystem, a target and a plurality of transmitters in accordance with anembodiment of the present invention;

[0013]FIG. 2 illustrates a block diagram of a passive coherent locationsystem in accordance with an embodiment of the present invention;

[0014]FIG. 3 illustrates a flowchart for pre-detection signal processingin a passive coherent location system in accordance with an embodimentof the present invention;

[0015]FIG. 4 illustrates a schematic view of a zero-doppler cancellationdevice in accordance with an embodiment of the present invention:

[0016]FIG. 5 illustrates a schematic view of a quadrature demodulationdevice in accordance with an embodiment of the present invention; and

[0017]FIG. 6 shows a flowchart for pre-detection signal processing inthe passive coherent location system in accordance with anotherembodiment of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0018] Reference will now be made in detail to the preferred embodimentof the present invention, examples of which are illustrated in theaccompanying drawings.

[0019] Passive coherent location (“PCL”) systems are passivesurveillance systems that utilizes multi-static wide area moving targetsurveillance sensors. PCL technology provides detection capabilitywithout transmitting energy at the targets of interest.

[0020] Passive radar systems, in contrast to conventional radar systems,exploit electromagnetic energy transmitted from uncontrolledilluminators, such as commercial broadcast frequency-modulated (“FM”)radio signals and television broadcast signals. Passive radar systemsreceive reflected signals that are the signals transmitted fromuncontrolled illuminators and reflected off the target of interest, anddirect path signals from the uncontrolled illuminators. The passiveradar systems extract the information about the target of interest bycorrelating the received reflected signals with the received direct pathsignals.

[0021]FIG. 1 depicts a block diagram of a PCL system, a target, and aplurality of transmitters in accordance with an embodiment of thepresent invention. FIG. 1 depicts a plurality of uncontrolledilluminators, or transmitters, 110, 112 and 114, a target of interest150 and a PCL system 100. Transmitters 110, 112 and 114 may includeuncontrolled narrowband illuminators, such as navigation aidtransmitters and/or repeaters and commercial television (“TV”) broadcasttransmitters and/or repeaters. Target 150 may be an aircraft.

[0022] Transmitters 110, 112 and 114 transmit electromagnetic energysignals in all directions. Some of the transmitted signals are reflectedby target 150 and scattered. PCL system 100 may receive some of thescattered signals, referred to as target path signals 130. Further, PCLsystem 100 receives some of the signals directly from transmitters 110,112 and 114. These signals may be known as reference path, or directpath, signals 140.

[0023]FIG. 2 depicts of PCL system 100 in accordance with an embodimentof the present invention. PCL system 100 includes an antenna 200, areceiving subsystem 202, an A/D converter subsystem 204, a processingsubsystem 206, and a display 208. PCL system 100 receives signalstransmitted from uncontrolled transmitters.

[0024] Antenna 200 receives reference path signal 140 from uncontrolledilluminators, including transmitters 110, 112, and 114. Antenna 200 alsoreceives target path signal 130 reflected from target 150. Antenna 200communicates reference path signal 140 and target path signal 130 toreceiving subsystem 202.

[0025] Receiving subsystem 202 receives and processes reference pathsignal 140 and target path signal 130 from antenna 200. Receivingsubsystem 202 may include a transducer. A/D converter subsystem 204receives the output of receiving subsystem 202 and outputs digitalsamples of the signals by sampling the signals at a desired samplingrate. A/D connector subsystem 204 forms a digital waveform using themagnitude of the analog signals at each sampling time. A/D convertersubsystem 204 may include an amplifier to amplify the received signal.

[0026] Processing subsystem 206 receives the digital samples of thereceived signals from A/D converter subsystem 204. Processing subsystem206 processes received reference signal 140 and target signal 130 toextract information about target interest 150. The processed informationmay include location, velocity, and acceleration information relating toa position of target 150.

[0027] Processing subsystem 206 may include sub-processors. Thesubprocessors may include a pre-detection signal processor 240 forremoving errors to provide optimized signals and a signal processor 242to extract information about target 150. Pre-detection signal processor240 performs the operations required to present estimated power spectraldensity (“PSD”) or cross ambiguity function (“CAF”) to detectionprocessing. Pre-detection signal processor 240 may include datade-interlever functional element 210, transformation functional element212, equalization functional element 914, zero-doppler cancellation(“ZDC”) functional element 216, quadrature demodulation functionalelement 218, reference beam regeneration functional element 220, inversetransformation functional element 222, beam formation functional element224, coherent processing interval (“CPI”) selection functional element226, motion compensation functional element 228, power spectral density(“PSD”) estimation functional element 230, cross ambiguity function(“CAF”) formation functional element 232, and RMS calculation functionalelement 234. Processing subsystem 200 may include a high performancecomputer with data storage capabilities that is programmed to performthe functions of the various disclosed elements. Alternatively, hardwareelements may be used as some or as all of the elements of thepre-detection processing subsystems.

[0028] Output device 208 receives and displays the information receivedfrom processing subsystem 206. Preferably, subsystems 202, 204, 206 and208 may be coupled through a high-speed network.

[0029]FIG. 3 depicts a flowchart for signal processing withpre-detection signal processor 240 in accordance with an embodiment ofthe present invention. Step 300 executes pre-detection signal processor240 receiving digital samples of target path signal 130 and referencepath signal 140 received at the antenna 200 from A/D converter subsystem204, as blocks of ADC time series data are multiplexed together. Theblocks of ADC time series data multiplexed are received by datade-interlever functional element 210.

[0030] Data de-interleaving functional element 210 extracts referencesignal 140 data and target signal 130 data from the input blocks of timeseries data as desired by the subsequent filtering operations, andapplies an appropriated ADC scale factor for parallel processing. Datade-interleaving functional element 210 passes the signals using twoprimary parallel paths. The two primary parallel paths address differenttypes of narrowband illuminators. The first path 302, including areference channel 370 and a target channel 372 shows the flow forzero-bandwidth signals typified by TV carriers. The second path 304,including a reference channel 380 and a target channel 382, depicts theflow for signals having some bandwidth for which correlation processingis generally superior in performance to the direct power spectraldensity (“PSD”) estimation used in the first path.

[0031] Referring to step 310 in the first path 302, data transformationfunctional element 212 receives reference signal 140 data and targetsignal 130 data through the reference channel 370 and the target channel372, respectively. Data transformation functional element 212 implementsdiscrete fourier transform (“DFT”), preferably by using fast fouriertransform (“FFT”) operation. The FFT operation transforms the input datafrom a time function to a frequency function. Preferably, anoverlap-save FFT operation may be implemented to cover all ranges. Theoverlap-save FFT operation is repeated independently for each timeseries data of interest, thus providing a unique “save” block and DFToutput for each of the target signal data and each of the referencesignal data. Preferably, a DFT length, N, may be chosen to be factoredinto a product of small integers (e.g., 2, 3, 4, or 5) so that anefficient FFT technique may be used to implement the 2N-length DFT.

[0032] Referring to step 312, equalization functional element 214receives the output of data transformation functional element 212through the reference channel and the target channel. Equalizationfunctional element 214 applies filters to each of reference signal 140data and target signal 130 data. The filters may minimize amplituderipple over about a 50 kHz band centered around the carrier frequency ofinterest, the target signal-to-reference differential group delay thatis a difference of the rate of phase shift with respect to frequencybetween target signal 130 data and reference signal 140 data, and thedifferential gain that is a difference of a ratio of signal-to-noiseratio and phase errors between the target signals. The filters may beobtained through an off-line calibration procedure. Equalizationfunctional element 214 compensates an intersymbol interference (“ISI”)that is an overlapping of successively transmitted signals within achannel due to its dispersion of the frequencies constituting thesignal. Equalization functional element 214 minimizes the probability oferror by compensating for channel distortion. The equalization proceduremay be repeated independently for each time series of the data.

[0033] Referring to step 314, zero-doppler cancellation functionalelement 216 implements an adaptive zero-doppler cancellation (“ZDC”), ora time-domain signal processing operation, to received target signal 130data via target channel 372B and reference channel 370B that minimizesthe portion of reference signal 140 data present in the target signal130 data. For each RF passband (distinct for each local oscillator(“LO”) tuning), the configurable input indicates whether or not ZDCshould be performed. If ZDC is to be performed, reference signal 140 isdesignated as either a single element A/D channel or an ordered list ofA/D channels with an associated set of beamforming coefficients.Referring to step 313, a delay may be introduced by a delay element tosignals within reference channel 370C.

[0034] Referring, to step 316, RMS (root mean square) bandwidthcalculation functional element 234 receives reference signal 140 datathrough reference channel 370C and estimates an RMS value of a bandwidthof reference 140 signal data. This value is desired in the calculationof the variance of the delay measurement performed that occurs later indetection and feature extraction processing.

[0035] Referring to step 318, quadrature demodulation functional element218 receives reference data 140 signal from equalization functionalelement 214 through a delay element and the output of zero-dopplercancellation functional element 216. Quadrature demodulation functionalelement 218 implements the time-domain signal processing operationschematically depicted in FIG. 5, as disclosed below.

[0036] Referring to step 320, inverse transformation functional element222 accepts target signal 130 data and reference signal 140 dataproduced by quadrature demodulation functional element 218 andimplements an inverse transformation. Preferably, B/2=N−(M_(EFF)−1)/2length blocks of complex-valued time series for the signals of interestmay be produced. Each of the target array element signals and thereference signals are independently processed. Preferably, the effectivefilter length is odd.

[0037] Referring to step 322, beam formation functional element 224accepts target signal 130 data produced by the proceeding functionalelements and combines them to form target beams that have selectivityalong specific lines of azimuth and elevation. Beam formation function322 may be an optional step.

[0038] Referring to step 324, (“CPI”) selection functional element 226receives target signal 130 and reference signal 140 produced from thepreceding functional elements and selects a CPI to accurately time-tagand synchronize detection report data from all receiver nodes within anetwork. The CPI selection is performed by basing the time-tags on(“GPS”) time and selecting CPIs centered on prescribed time instants.This time interval may range from about tens to about hundreds ofmilliseconds. GPS time is latched periodically from a GPS receiver andassociated with the A/D sample nearest in time. With this GPS time mark,all buffered A/D data in memory can be time-tagged accurately using thesampling rate and number of samples from the GPS time mark.

[0039] Referring to step 326, motion compensation functional element 228receives the signals from CPI selection functional element 226 andimplements motion compensation by accepting tracker feedback for atarget-of-interest (“TOI”) and enhancing the detection performance forthe TOI by compensating for its motion over the CPI. The motioncompensation operation may be performed as one of the processing controloptions. Motion compensation function element 326 implements the motioncompensation when the time difference between the state vector time andthe CPI time does not exceed a threshold,

|t _(m) −t ₀|<η_(mot).

[0040] When the motion compensation option is exercised, the feedback isthe state vector that is provided periodically after the TOI has beenidentified as such in the tracker function. The state vector feedback isdenoted by the vector triplet

X _(TOI) [t ₀]=({overscore (R)} ₀ {overscore (V)} ₀ , {overscore (A)}₀),

[0041] where R₀, V₀, and A₀ denote the target's position, velocity, andacceleration vectors at time t₀.

[0042] Referring to step 328, power spectral density (“PSD”) estimationfunctional element 230 receives target signal 130 and reference signal140 produced from the preceding functional elements and estimates thepower spectral density. In one embodiment, a windowed periodogram iscomputed as the estimate of the PSD. Other spectral density estimatorsmay be used. Periodogram is based on the discrete Fourier transform.Periodogram displays the presence of a sinusoid near one frequency valueas a distinct peak in the spectrum. In one embodiment, the periodogrammay be computed according to $\begin{matrix}{{Y\lbrack k\rbrack} = {\frac{1}{N}{{{CDFT}_{n}\left\{ {{X\lbrack n\rbrack}{W\lbrack n\rbrack}} \right\}}}^{2}}} & \quad & {{{{for}\quad k} = 0},1,\ldots \quad,{N - 1},}\end{matrix}$

[0043] where the data within the CPI is denoted as X [n], n=0, 1, . . ., N−1 and the window is denoted as W[n], n=0, 1, . . . , N=1.

[0044] The window function is selected via the configuration parameterWINDOP.

[0045] The Hamming window and the Blackman window may be used.

[0046] The Hamming window may be defined by $\begin{matrix}{{W\lbrack n\rbrack} = {0.54 - {0.46\quad {\cos \left( \frac{2\quad \pi \quad \pi}{N - 1} \right)}}}} & {{{{for}\quad n} = 0},1,\ldots \quad,{N - 1}}\end{matrix}$

[0047] The power gains of the Hamming window are −5.4 dB for a constantamplitude signal 0.5 and −4.0 dB for a white noise sequence.

[0048] The Blackman window may be defined by $\begin{matrix}{{W\lbrack n\rbrack} = {a_{0} - {a_{1}{\cos \left( \frac{2\quad \pi \quad \pi}{N - 1} \right)}} + {a_{2}\quad {\cos \left( \frac{4\quad \pi \quad \pi}{N - 1} \right)}}}} & {{{{for}\quad n} = 0},1,\ldots \quad,{N - 1}}\end{matrix}$

[0049] where a₀=0.42323, a₁=0.49755, a₂=0.07922.

[0050] The power gains of the Blackman window are −7.5 dB for a constantamplitude signal and −5.1 dB for a white noise sequence. In thedetection processing step, the total noise power is the average of theperiodogram components, where the average is taken over the binsclassified as “noise bins”.

[0051] For each link, the power spectral density is estimated after thesignals are modulated to compensate for the motion. The detector acceptsdetection reports having doppler within a selectable interval about thepredicted doppler for the target for each link “k”, i.e., whenever

|f _(d,k,m+λ) _(i) ⁻¹ {overscore (V)} _(m) ·{overscore (B)}_(k,m)|<η_(mow).

[0052] Separately, at the same time when reference signal 140 and targetsignal 130 is processed in first path 302, the signals are processed insecond path 304 for the correlation processing, as depicted in FIG. 3.The signal processing steps in second path 304 are disclosed below.

[0053] Referring to step 330 of second path 304, data transformationfunctional element 212 receives reference signal 140 data and targetsignal 130 data through reference channel 380 and target channel 382,respectively. Data transformation functional element 212 implementsdiscrete Fourier transform, preferably by using a fast Fourier transformoperation, required by the subsequent filtering operations, as disclosedabove.

[0054] Referring to step 332, equalization functional element 214receives the output of data transformation functional element 212through reference channel 380 and target channel 382. Equalizationfunctional element 214 applies filters to each of reference signal 140data and target signal 130 data to compensate for channel distortion.The equalization procedure may be repeated independently for each timeseries of the data.

[0055] Referring to step 334, zero-doppler cancellation functionalelement 216 implements an adaptive zero-doppler cancellation operationschematically depicted in FIG. 5 to received target signal 130 data tominimize the portion of reference signal 140 data present in targetsignal 130 data via target channel 382B and reference channel 380B.Referring to step 333, a delay may be introduced by a delay element tosignals within reference channel 380C.

[0056] Referring to step 336, root mean square bandwidth calculationfunctional element 234 receives reference signal 140 data throughreference channel 380C and estimates the RMS value of a bandwidth ofreference signal 140 data. This value is desired in the calculation ofthe variance of the delay measurement performed in subsequent detectionand feature extraction processing.

[0057] Referring to step 338, quadrature demodulation functional element218 receives reference signal 140 from equalization function element 214through the delay element of step 333 and the output of zero-dopplercancellation functional element 216. Quadrature demodulation functionalelement 218 implements the time-domain signal processing operationschematically disclosed with regard to FIG. 5.

[0058] Referring to step 340, inverse transformation functional element222 accepts target signal 130 data and reference signal 140 dataproduced by quadrature demodulation functional element 218 andimplements an inverse transformation operation. Preferably,B/2=N−(M_(EFF)−1)/2 length blocks of complex-valued time series for thesignals of interest may be produced. Each of the target array elementsignals and the reference signal are independently processed.Preferably, the effective filter length is odd.

[0059] Referring to step 342, beam formation functional element 224accepts target signal 130 data produced by the proceeding functionalelements and combines them to form target beams which have selectivityalong specific lines of azimuth and elevation. The beam formationfunction may be optional.

[0060] Referring to step 344, CPI selection functional element 226receives target signal 130 and reference signal 140 produced in thepreceding functional elements and selects a CPI to accurately time-tagand synchronize detection report data from all receiver nodes within anetwork, as disclosed above. Referring to step 346, motion compensationfunctional element 228 receives the signals from CPI selectionfunctional element 226 and implements motion compensation by acceptingtracker feedback for a target-of-interest (“TOI”) and enhancing thedetection performance for the TOI by compensating for its motion overthe CPI. The motion compensation operation may be optional.

[0061] Referring to step 350 in second path 304, cross ambiguityfunction formation estimation functional element 232 receives targetsignal 130 and reference signal 140 produced from the precedingfunctional elements through a target channel 380C and a referencechannel 380D, respectively. Cross ambiguity function formationestimation functional element 232 computes a cross-ambiguity over theCPI of T samples for the each of the target signals. The cross ambiguityfunction extracts the commonalties between two signals or systems todetermine the existence or structure of these commonalties. The coherentprocessing interval may be overlapped by some factor, 1-1/ρ, ρ=2, 4, andthe like.

[0062] Separately, in step 348, power spectral density estimationfunctional element 230 receives reference signal 140 produced frompreceding functional elements through a reference channel 382C andestimates the power spectral density.

[0063]FIG. 4 depicts an adaptive zero-doppler cancellation device withinpre-detection signal processor 240 in accordance with an embodiment ofthe present invention. Zero-doppler cancellation functional element 216receives time series target signal 130 data and time series referencesignal 140 data through a reference channel 370B and a target channel372B, respectively. Target channel 372B routes target signal 130 throughdelay element 404. The first received reference signal data is filteredwith respect to the first target signal data received by filter 410. Thefiltered first reference signal data received is combined with the firstreceived target signal data to minimize the portion of the firstreference signal data received present in the first received targetsignal data. Then, filter update functional element 412 updates filter410 with respect to the second received target signal data by comparingfilter 410 with the second received target signal data. The secondreceived reference signal data through reference channel 370B isfiltered with filter 410 that is updated with respect to the secondreceived target signal data. Then, the filtered second receivedreference signal data is combined with the second target signal data.Filter 410 is updated continuously by filter update functional element412 with respect to each of the time series of target signal 130 datareceived through target channel 372B by comparing filter 410 to the eachof the time series. The disclosed zero-doppler cancellation operationmay be repeated independently for each element time series. Referencesignal 140 data is adaptively filtered. Each of the filtered timesseries of reference signal 140 data is combined with the each of thetime series of target signal 130 data. Filter 410 preferably includes anadaptive Wiener filter. By applying the disclosed adaptive zero-dopplercancellation, more accurate target signal data for a moving target begenerated.

[0064]FIG. 5 depicts a schematic view of a quadrature demodulationdevice in accordance with an embodiment of the present invention. Thephase of the real-valued signal data may be shifted by multiplying thedata with exp ${\exp \left( {{- j}\quad \frac{\pi}{2}m} \right)}.$

[0065] The real-valued signal data that has a center frequency of π/2 isdemodulated, filtered with a low-pass filter 512, such as a (“FIR LPF”),and decimated to produce complex-valued signal data. The real-valuedinput times series data is demodulated, filtered and decimated toproduce a complex, or quadrature, representation of the time series thatis centered at zero radians per sample and has a reduced sample rate.Decimation element 514 may decimate the input time series data.

[0066] By finding a complex envelope, the real-valued signal data, whichis a low-pass function with the in-phase component and the quadraturecomponent in the quadrature representation, analysis of a band-passsystem, that is complicated by the presence of the multiplying factorexp $\exp \left( {{- j}\quad \frac{\pi}{2}m} \right)$

[0067] is replaced by an equivalent, but simpler, low-pass analysis thatretains the essence of the filtering processes. The demodulating,filtering and decimating depicted in FIG. 5 may be combined into asignal using more memory efficient operation. In addition, if theeffective filter length is odd, the phase accumulator may assume valuesof multiples of π/2, so that the multiplication by the phase accumulatorcan be implemented as a sign change. Quadrature demodulation functionalelement 218 implements the signal processing operation in FIG. 5 to thereceived target signal data and the received reference signal 140 data.

[0068]FIG. 6 depicts a flowchart for pre-detection signal processing inaccordance with another embodiment of the present invention. The signalprocessing operations disclosed below may occur using pre-detectionprocessor 240. Pre-detection processor 240, however, may use analternate approach of constant modulus reference regeneration asdisclosed in U.S. Pat. No. 5,604,503, which is hereby incorporated byreference, in the absence of a reference channel.

[0069] Referring to step 600, pre-detection signal processor 240receives digital samples of target path signal 130 and reference pathsignal 140 from A/D converter subsystem 204, as blocks of ADC timeseries data multiplexed together. The blocks of ADC time series data arereceived by data de-interlever functional element 210. According to theembodiments disclosed with reference to FIG. 6, data de-interleavingfunctional element 210 should not extract reference signal 140 data andtarget signal 130 data from the input signal data blocks of time seriesdata. Data de-interleaving functional element 210 passes the signalsusing two parallel paths, first path 602 and second path 604. First path602 depicts the flow for zero-bandwidth signals typified by TV carriers.Second path 604 depicts the flow for signals having some bandwidth forwhich correlation processing is superior in performance to the direct“PSD” estimation used in first path 602.

[0070] The signal processing steps in first path 602 are disclosedbelow. Referring to step 610, data transformation functional element 212receives the input signal with target signal 130 data and referencesignal 140 data through first path 602. The data may be received overtarget channel 672 and reference channel 670, respectively. Datatransformation functional element 212 implements discrete Fouriertransform operations, preferably by using fast Fourier transform (“FFT”)operations, desired by the subsequent filtering operations. The FFToperations transform the input data from a time function to a frequencyfunction. Preferably, an overlap-save FFT operation may be implementedto cover all possible ranges of frequencies. The overlap-save FFToperation is repeated independently for each time series data ofinterest, thus providing an unique “save” block and “DFT” output for theinput signal data. Preferably, a DFT length, N, may be chosen to befactored into a product of small integers (e.g., 2, 3, 4, or 5) so thatan efficient FFT technique may be used to implement a 2N-length DFT.

[0071] Referring to step 612, equalization functional element 214receives the output of data transformation functional element 212 andapplies unique filters to the output. Referring to step 614, quadraturedemodulation functional element 218 receives the output of equalizationfunctional element 214 and implements the time-domain signal processingoperations disclosed with reference to FIG. 5, to produce a complexrepresentation of the time series that is centered at zero radians persample.

[0072] Referring to step 616, reference beam regeneration functionalelement 220 receives the output of the quadrature demodulationfunctional element 218 and estimates reference signal 140 (i.e., the D-Psignal) and target signal 130 (i.e., the T-P signal) as disclosed inU.S. Pat. No. 5,604,503, which is hereby incorporated by reference.

[0073] Referring to step 618, zero-doppler cancellation functionalelement 216 receives target signal 130 and reference signal 140estimated by reference beam regeneration functional element 220 througha target channel 672B and a reference channel 670B, respectively. ZDCfunctional element 216 implements the time-domain signal processingoperations disclosed above with reference to FIG. 4. Referring to step617, a delay may be introduced by a delay element to signals withinreference channel 670C.

[0074] Referring to step 620, RMS bandwidth calculation functionalelement 234 estimates the bandwidth of reference signal 140 withinreference channel 670C. The estimated value may be desired in thecalculation of the variance of the delay measurement performed insubsequent detection and feature extraction processing.

[0075] Referring to step 622, the data of reference signal 140 andtarget signal 130 are received at inverse transformation functionalelement 222. As disclosed above, inverse transformation functionalelement 222 may accept the N-length DFTs of the target array elementsignals produced by quadrature demodulation functional element 218, asdisclosed above, and the N-length DFTs of reference signal 140. Inversetransformation functional element 222 produces B/2=N−(M_(EFF)−1)/2length blocks of complex-valued time series for signals 130 and 140. Thetarget array element signals and reference signal 140 may be processedindependently as disclosed above. Preferably, the effective lengthfilter length is odd.

[0076] Referring to step 624, beamformation functional element 224accepts the array element signals of target signal 130 or referencesignal 140 produced by the preceding functional elements. Beamformationfunctional element 224 combines the array element signals to formsignals that have selectivity along specific lines of azimuth andelevation. This step may be optional in the signal processingoperations.

[0077] Referring to step 626, CPI selection functional element 226 maylatch periodically global positioning system (“GPS”) time for a GPSreceiver and associate the time with the A/D sample nearest in time.Using the GPS time mark, buffered A/D data in memory coupled topre-detection processor 240 may time-tagged accurately using the samplerate and the number of samples from the mark. Thus, CPI selectionfunctional element 226 may time-tag and synchronize detection reportdata from all receiver nodes within a network by basing the time-tags onGPS time and selecting CPIs centered on prescribed time instants.

[0078] Referring to step 628, motion compensation functional element 228accepts tracker feedback for the TOI and enhances the detectionperformance for the TOI by compensating for its motion over the CPI. Thefeedback from step 628 may be the state vector that is providedperiodically after the TOI has been identified as such in the trackerfunction, as disclosed with reference to step 326 in FIG. 3. Step 628may be optional. Referring to step 630, power spectral densityfunctional element 230 computes a windowed periodogram as the estimateof the power spectral density (“PSD”), as disclosed above with referenceto step 328 in FIG. 3.

[0079] The processing steps for second path 604 receive reference signal140 in reference channel 680 and target signal 130 in target channel682. Second path 604 follows the order of first-path 602, except for afew variations. Referring to step 631, data transformation functionalelement 212 implements discrete Fourier transform operations, preferablyby using fast Fourier transform operations, desired by the subsequentfiltering operations. The FFT transforms the input data from a timefunction to a frequency function. Preferably, an overlap-save FFToperation may be implemented to cover all possible ranges offrequencies. The overlap-save FFT operation is repeated independentlyfor each time series data of interest, thus providing an unique “save”block and “DFT” output for the input signal data. Preferably, a DFTlength, N, may be chosen to be factored into a product of small integers(e.g., 2, 3, 4, or 5) so that an efficient FFT technique may be used toimplement a 2N-length DFT.

[0080] Referring to step 632, equalization functional element 214receives the output of data transformation functional element 212 andapplies unique filters to the output. Referring to step 634, quadraturedemodulation functional element 218 receives the output of equalizationfunctional element 214 and implements the time-domain signal processingoperations disclosed with reference to FIG. 5, to produce a complexrepresentation of the time series that is centered at zero radians persample.

[0081] Referring to step 636, reference beam regeneration functionalelement 220 receives an output of quadrature demodulation functionalelement 218 and estimates reference signal 140 (i.e., the D-P signal)and target signal 130 (i.e., the T-P signal) as disclosed in U.S. Pat.No. 5,604,503, which is hereby incorporated by reference.

[0082] Referring to step 638, zero-doppler cancellation functionalelement 216 receives target signal 130 and reference signal 140estimated by reference beam regeneration functional element 220 througha target channel 682B and a reference channel 680B, respectively. ZDCfunctional element 216 implements the time-domain signal processingoperations disclosed above with reference to FIG. 4. Referring to step637, a delay may be introduced by a delay element to signals withinreference channel 680C.

[0083] Referring to step 640, RMS bandwidth calculation functionalelement 234 estimates the bandwidth of reference signal 140 withinreference channel 680C. The estimated value may be desired in thecalculation of the variance of the delay measurement performed insubsequent detection and feature extraction processing.

[0084] Referring to step 622, the data of reference signal 140 andtarget signal 130 are received at inverse transformation functionalelement 222. As disclosed above, inverse transformation functionalelement 222 may accept the N-length DFTs of the target array elementsignals produced by quadrature demodulation functional element 218, asdisclosed above, and the N-length DFTs of reference signal 140. Inversetransformation functional element 222 produces B/2=N−(M_(EFF)−1)/2length blocks of complex-valued time series for signals 130 and 140. Thetarget array element signals and reference signal 140 may be processedindependently as disclosed above. Preferably, the effective lengthfilter length is odd.

[0085] Referring to step 644, beamformation functional element 224accepts the array element signals of target signal 130 or referencesignal 140 produced by the preceding functional elements. Beamformationfunctional element 224 combines the array element signals to formsignals that have selectivity along specific lines of azimuth andelevation. This step may be optional in the signal processingoperations.

[0086] Referring to step 648, motion compensation functional element 228accepts tracker feedback for the TOI and enhances the detectionperformance for the TOI by compensating for its motion over the CPI. Thefeedback from step 648 may be the state vector that is providedperiodically after the TOI has been identified as such in the trackerfunction, as disclosed with reference to step 326 in FIG. 3. Step 648may be optional.

[0087] Referring to step 650, cross ambiguity function (“CAF”) formationestimation functional element 232 receives target signal 130 andreference signal 140 produced from the preceding functional elementsthrough a target channel 682C and a reference channel 680D,respectively. CAF formation estimation functional element 232 computes across-ambiguity over the CPI of T samples for each of the targetsignals, such as target signal 130. The CAF extracts the commonalitiesbetween two signals or systems to determine the existence or structureof these commonalities. The CPI may be overlapped by some factor, suchas 1−1/ρ, ρ=2, 4, and the like. Referring to step 652, power spectraldensity functional element 230 computes a windowed periodogram as theestimate of the power spectral density (“PSD”), as disclosed above withreference to step 328 in FIG. 3.

[0088] The filtering operations performed prior to beamformation, suchas equalization, zero-doppler cancellation, quadrature demodulation andinverse transformation, may be implemented using overlap-save fastconvolution operations in order for contiguous blocks of input timeseries data to produce contiguous blocks of output time series data justprior to the selection of the CPI and formation of the estimated PSD andCAF functions. The overlap-save filtering operations may equalize thetarget array element signals and minimize the amount of reference signalin each target array element signal.

[0089] Additionally, the overlap-save filtering operations may produce acomplex representation of the target element signal data that iscentered around zero radians per sample. The disclosed functionalelements operate in real-time. As can be appreciated, pre-detectionsignal processing in the present invention may cancel interfering signalenergy from the target array element. Additionally, the target arrayelement signals may be transformed into directed beams along specifiedazimuth angles.

[0090] It will be apparent to those skilled in the art that variousmodifications and variations can be made in the disclosed embodiments ofthe present invention without departing from the spirit or scope of theinvention. Thus, it is intended that the present invention covers themodifications and variations of this invention provided that they comewithin the scope of any claims and their equivalents.

1-18. (Cancelled)
 19. A method for narrowband pre-detection signalprocessing for passive coherent location applications comprising:receiving an input signal including a target signal and a referencesignal; and passing the input signal in two paths for parallelprocessing, wherein each of the paths includes a target channel and areference channel for the target signal and the reference signal,respectively, and one of the paths is for correlation signal processing.20. The method according to claim 19, wherein the method furtherincludes selecting a coherent processing interval in the each of thepaths.
 21. The method according to claim 20, wherein the method furtherincludes compensating for motion by accepting tracker feedback for atarget and compensating for motion over the coherent processing intervalin the each of the paths.
 22. The method according to claim 21, whereinthe method further includes estimating a power spectral density afterthe motion compensation.
 23. The method according to claim 19, whereinthe method further includes estimating a power spectral density for theeach of the paths and estimating a cross ambiguity function for one ofthe paths simultaneously.
 24. The method according to claim 23, whereinHamming window is used in estimating the power spectral density.
 25. Themethod according to claim 23, wherein Blackman window is used inestimating the power spectral density.
 26. The method according to claim19, wherein the method further includes estimating the reference signaland the target signal from the input signal.
 27. The method according toclaim 26, wherein estimating reference signal includes estimating amagnitude of the reference signal from the first input signal.
 28. Themethod according to claim 26, wherein the method further includesdemodulating and producing complex-valued representation of the inputsignal before estimating the reference signal and the target signal. 29.The method according to claim 28, wherein the method further includesdecimating the complex-valued representation of the input signal.
 30. Amethod for narrowband pre-detection signal processing for passivecoherent location applications, comprising: receiving an input signalincluding a target signal reflected from a target; selecting a coherentprocessing interval; and compensating for motion by accepting trackerfeedback for a target and compensating for motion over the coherentprocessing interval.
 31. The method according to claim 30, wherein themethod further includes estimating a power spectral density after themotion compensation.
 32. A method for narrowband pre-detection signalprocessing in passive coherent location applications, comprising:receiving an input signal; extracting a target signal and a referencesignal from the input signal; passing the target signal and thereference signal in two paths for parallel processing, wherein the eachof the paths includes a target channel and a reference channel for thetarget signal and the reference signal, respectively; implementing atransformation operation on the target signal and the reference signal;compensating the transformed target signal and the transformed referencesignal for channel distortion; demodulating and forming complex-valuedrepresentations of the reference signal and the target signal;implementing an inverse; and estimating a power spectral density in oneof the paths and estimating a power spectral density and a crossambiguity function in the other paths.
 33. The method according to claim32, wherein the method further includes reducing a portion of thereference signal in the target signal by adaptively filtering thereference signal with respect to the target signal and combining withthe target signal.
 34. The method according to claim 32, the methodfurther comprising: selecting a coherent processing interval; andcompensating for motion by accepting tracker feedback for a target andcompensating for motion over the coherent processing interval.
 35. Amethod for narrowband pre-detection signal processing in passivecoherent location applications, comprising: receiving an input signal;passing the input signal in two paths for parallel processing;implementing a transformation operation on the input signal;compensating the transformed input signal for channel distortion;demodulating and forming complex-valued representations of thecompensated input signal; estimating a reference signal and a targetsignal from the demodulated input signal, wherein estimating thereference signal includes estimating a magnitude of the reference signalfrom the input signal; implementing an inverse transformation; andestimating a power spectral density in one of the paths and estimating apower spectral density and a cross ambiguity function in the otherpaths.
 36. The method according to claim 35, wherein the method furtherincludes: reducing a portion of the estimated reference signal in theestimated target signal by adaptively filtering the estimated referencesignal with respect to the estimated target signal and combining withthe estimated target signal.
 37. The method according to claim 35, themethod further comprising: selecting a coherent processing interval; andcompensating for motion by accepting tracker feedback for a target andcompensating for motion over the coherent processing interval. 38.(Canceled)
 39. A system for narrowband pre-detection signal processingfor passive coherent location applications comprising: means forreceiving an input signal including a target signal and a referencesignal; and means for passing the input signal in two paths for parallelprocessing, wherein each of the paths includes a target channel and areference channel for the target signal and the reference signal,respectively, and one of the paths is for correlation signal processing.40. A system for narrowband pre-detection signal processing for passivecoherent location applications, comprising: means for receiving an inputsignal including a target signal reflected from a target; means forselecting a coherent processing interval; and means for compensating formotion by accepting tracker feedback for a target and compensating formotion over the coherent processing interval.
 41. A system forenarrowband pre-detection signal processing in passive coherent locationapplications, comprising: means for receiving an input signal; means forextracting a target signal and a reference signal from the input signal;means for passing the target signal and the reference signal to a firstand second paths for parallel processing, wherein the each of the pathsincludes a target channel and a reference channel for the target signaland the reference signal, respectively; means for implementing atransformation operation on the target signal and the reference signal;means for compensating the transformed target signal and the transformedreference signal for channel distortion; means for demodulating andforming complex-valued representations of the reference signal and thetarget signal; means for implementing an inverse; and means forestimating a power spectral density in one of the paths and estimating apower spectral density and a cross ambiguity function in the otherpaths.
 42. A system for narrowband pre-detection signal processing inpassive coherent location applications, comprising: means for receivingan input signal; means for passing the input signal in two paths forparallel processing; means for implementing a transformation operationon the input signal; means for compensating the transformed input signalfor channel distortion; means for demodulating and formingcomplex-valued representations of the compensated input signal; meansfor estimating a reference signal and a target signal from thedemodulated input signal, wherein estimating the reference signalincludes estimating a magnitude of the reference signal from the inputsignal; means for implementing an inverse transformation; and means forestimating a power spectral density in one of the paths and estimating apower spectral density and a cross ambiguity function in the otherpaths.